{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\ondre\OneDrive\Plocha\RnP\Revisions\Dataverse\svr_jeps_replication_log4.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}20 Jan 2023, 13:21:43

{com}. **************************************************************

. 
. *** Replication code for "The 'Commitment trap' Revisited: ***

. 
. *** Experimental Evidence on Ambiguous Nuclear Threats" by ***

. 
. *** Michal Smetana, Marek Vranka, and Ondrej Rosendorf     ***

. 
. **************************************************************

. 
. 
. 
. *** The code was written in Stata 17.0 BE-Basic Edition ***

. 
. 
. 
. *** Please reach out to ondrej.rosendorf@fsv.cuni.cz if you have any questions concerning this replication file ***

. 
. 
. 
. *** IMPORTANT: This file is accompanied by the svr_jeps_replication_data4 dataset ***

. 
. 
. 
. *** Before proceeding with the replication, please make sure that the "coefplot", "catplot" and "asdoc" package is installed ***

. 
. 
. 
. *** To install the coefplot package, use the following command ***

. 
. 
. 
. ssc install coefplot, replace
{txt}checking {hilite:coefplot} consistency and verifying not already installed...
all files already exist and are up to date.

{com}. 
. 
. 
. *** To install the catplot package, use the following command ***

. 
. 
. 
. ssc install catplot, replace
{txt}checking {hilite:catplot} consistency and verifying not already installed...
all files already exist and are up to date.

{com}. 
. 
. 
. *** To install the asdoc package, use the following command ***

. 
. 
. 
. ssc install asdoc, replace
{txt}checking {hilite:asdoc} consistency and verifying not already installed...
all files already exist and are up to date.

{com}. 
. 
. 
. *** Setting the output scheme to black and white ***

. 
. 
. 
. set scheme s1mono

. 
. 
. 
. *************************************************

. 
. *** Replication of the results in Appendix 13 ***

. 
. *************************************************

. 
. 
. 
. *** Appendix 13, Table 1 (contingency tables) - President over treatment ***

. 
. 
. 
. * Generating a labelled version of the scenario_n variable

. 
. recode scenario_n (0=0 "Control") (1=1 "Ambiguous threat") (2=2 "Explicit threat"), generate(scenario_n_label)
{txt}(0 differences between {bf:scenario_n} and {bf:scenario_n_label})

{com}. 
. 
. 
. * Generating a labelled version of the president variable

. 
. recode president (1=1 "Trump") (2=2 "Biden") (3=3 "Republican") (4=4 "Democrat") (5=5 "Generic"), generate(president_label)
{txt}(0 differences between {bf:president} and {bf:president_label})

{com}. 
. 
. 
. * Generating and exporting cross-tabs of president_label over scenario_n_label

. 
. asdoc tab scenario_n_label president_label, title(Table 1: Cross-tabulations of associations across treatments) row chi2 save(A13T01.rtf)
{txt}
{c TLC}{hline 16}{c TRC}
{c |} Key{col 18}{c |}
{c LT}{hline 16}{c RT}
{c |}{space 3}{it:frequency}{col 18}{c |}
{c |}{space 1}{it:row percentage}{col 18}{c |}
{c BLC}{hline 16}{c BRC}

       RECODE of {c |}
      scenario_n {c |}       RECODE of president (President)
    (scenario_n) {c |}     Trump      Biden  Republica   Democrat {c |}     Total
{hline 17}{c +}{hline 44}{c +}{hline 10}
         Control {c |}{res}        21         10         28         12 {txt}{c |}{res}       202 
                 {txt}{c |}{res}     10.40       4.95      13.86       5.94 {txt}{c |}{res}    100.00 
{txt}{hline 17}{c +}{hline 44}{c +}{hline 10}
Ambiguous threat {c |}{res}        75          6         36          7 {txt}{c |}{res}       198 
                 {txt}{c |}{res}     37.88       3.03      18.18       3.54 {txt}{c |}{res}    100.00 
{txt}{hline 17}{c +}{hline 44}{c +}{hline 10}
 Explicit threat {c |}{res}        72          7         42          4 {txt}{c |}{res}       200 
                 {txt}{c |}{res}     36.00       3.50      21.00       2.00 {txt}{c |}{res}    100.00 
{txt}{hline 17}{c +}{hline 44}{c +}{hline 10}
           Total {c |}{res}       168         23        106         23 {txt}{c |}{res}       600 
                 {txt}{c |}{res}     28.00       3.83      17.67       3.83 {txt}{c |}{res}    100.00 


                 {txt}{c |} RECODE of
                 {c |} president
       RECODE of {c |} (President
      scenario_n {c |}     )
    (scenario_n) {c |}   Generic {c |}     Total
{hline 17}{c +}{hline 11}{c +}{hline 10}
         Control {c |}{res}       131 {txt}{c |}{res}       202 
                 {txt}{c |}{res}     64.85 {txt}{c |}{res}    100.00 
{txt}{hline 17}{c +}{hline 11}{c +}{hline 10}
Ambiguous threat {c |}{res}        74 {txt}{c |}{res}       198 
                 {txt}{c |}{res}     37.37 {txt}{c |}{res}    100.00 
{txt}{hline 17}{c +}{hline 11}{c +}{hline 10}
 Explicit threat {c |}{res}        75 {txt}{c |}{res}       200 
                 {txt}{c |}{res}     37.50 {txt}{c |}{res}    100.00 
{txt}{hline 17}{c +}{hline 11}{c +}{hline 10}
           Total {c |}{res}       280 {txt}{c |}{res}       600 
                 {txt}{c |}{res}     46.67 {txt}{c |}{res}    100.00 

{txt}          Pearson chi2({res}8{txt}) = {res} 63.5403  {txt} Pr = {res}0.000
Click to Open File:  {browse "A13T01.rtf"}

{com}. 
. 
. 
. *** Appendix 13, Table 2 (contingency tables) - Trump over treatment ***

. 
. 
. 
. * Generating a simplified version of the president variable

. 
. gen trump = 0

. 
. replace trump = 1 if president == 1
{txt}(168 real changes made)

{com}. 
. 
. 
. * Generating a labelled version of the trump variable

. 
. recode trump (0=0 "Not Trump") (1=1 "Trump"), generate(trump_label)
{txt}(0 differences between {bf:trump} and {bf:trump_label})

{com}. 
. 
. 
. * Generating a simplified version of the preference_ordinal variable

. 
. gen preference_adjusted = 0

. 
. replace preference_adjusted = 1 if preference_ordinal == 3
{txt}(51 real changes made)

{com}. 
. replace preference_adjusted = 1 if preference_ordinal == 4
{txt}(22 real changes made)

{com}. 
. 
. 
. * Generating a labelled version of the preference_adjusted variable

. 
. recode preference_adjusted (0=0 "Prefer conventional") (1=1 "Prefer nuclear"), generate(preference_adjusted_label)
{txt}(0 differences between {bf:preference_adjusted} and {bf:preference_adjusted_label})

{com}. 
. 
. 
. * Generating cross-tabs for trump over preference by scenario

. 
. asdoc tab preference_adjusted_label trump_label if scenario_n_label==0, title(Table 2a: Cross-tabulations of response preference across associations - Control) col chi2 save(A13T02)
{txt}
{c TLC}{hline 19}{c TRC}
{c |} Key{col 21}{c |}
{c LT}{hline 19}{c RT}
{c |}{space 5}{it:frequency}{col 21}{c |}
{c |}{space 1}{it:column percentage}{col 21}{c |}
{c BLC}{hline 19}{c BRC}

          RECODE of {c |}    RECODE of trump
preference_adjusted {c |} Not Trump      Trump {c |}     Total
{hline 20}{c +}{hline 22}{c +}{hline 10}
Prefer conventional {c |}{res}       158         17 {txt}{c |}{res}       175 
                    {txt}{c |}{res}     87.29      80.95 {txt}{c |}{res}     86.63 
{txt}{hline 20}{c +}{hline 22}{c +}{hline 10}
     Prefer nuclear {c |}{res}        23          4 {txt}{c |}{res}        27 
                    {txt}{c |}{res}     12.71      19.05 {txt}{c |}{res}     13.37 
{txt}{hline 20}{c +}{hline 22}{c +}{hline 10}
              Total {c |}{res}       181         21 {txt}{c |}{res}       202 
                    {txt}{c |}{res}    100.00     100.00 {txt}{c |}{res}    100.00 

{txt}          Pearson chi2({res}1{txt}) = {res}  0.6533  {txt} Pr = {res}0.419
Click to Open File:  {browse "A13T02.doc"}

{com}. 
. asdoc tab preference_adjusted_label trump_label if scenario_n_label==1, title(Table 2b: Cross-tabulations of response preference across associations - Ambiguity) col chi2 save(A13T02) 
{txt}(File A13T02.doc already exists, option {bf:append} was assumed)

{c TLC}{hline 19}{c TRC}
{c |} Key{col 21}{c |}
{c LT}{hline 19}{c RT}
{c |}{space 5}{it:frequency}{col 21}{c |}
{c |}{space 1}{it:column percentage}{col 21}{c |}
{c BLC}{hline 19}{c BRC}

          RECODE of {c |}    RECODE of trump
preference_adjusted {c |} Not Trump      Trump {c |}     Total
{hline 20}{c +}{hline 22}{c +}{hline 10}
Prefer conventional {c |}{res}       108         65 {txt}{c |}{res}       173 
                    {txt}{c |}{res}     87.80      86.67 {txt}{c |}{res}     87.37 
{txt}{hline 20}{c +}{hline 22}{c +}{hline 10}
     Prefer nuclear {c |}{res}        15         10 {txt}{c |}{res}        25 
                    {txt}{c |}{res}     12.20      13.33 {txt}{c |}{res}     12.63 
{txt}{hline 20}{c +}{hline 22}{c +}{hline 10}
              Total {c |}{res}       123         75 {txt}{c |}{res}       198 
                    {txt}{c |}{res}    100.00     100.00 {txt}{c |}{res}    100.00 

{txt}          Pearson chi2({res}1{txt}) = {res}  0.0547  {txt} Pr = {res}0.815
Click to Open File:  {browse "A13T02.doc"}

{com}. 
. asdoc tab preference_adjusted_label trump_label if scenario_n_label==2, title(Table 2c: Cross-tabulations of response preference across associations - Explicit) col chi2 save(A13T02)
{txt}(File A13T02.doc already exists, option {bf:append} was assumed)

{c TLC}{hline 19}{c TRC}
{c |} Key{col 21}{c |}
{c LT}{hline 19}{c RT}
{c |}{space 5}{it:frequency}{col 21}{c |}
{c |}{space 1}{it:column percentage}{col 21}{c |}
{c BLC}{hline 19}{c BRC}

          RECODE of {c |}    RECODE of trump
preference_adjusted {c |} Not Trump      Trump {c |}     Total
{hline 20}{c +}{hline 22}{c +}{hline 10}
Prefer conventional {c |}{res}       114         65 {txt}{c |}{res}       179 
                    {txt}{c |}{res}     89.06      90.28 {txt}{c |}{res}     89.50 
{txt}{hline 20}{c +}{hline 22}{c +}{hline 10}
     Prefer nuclear {c |}{res}        14          7 {txt}{c |}{res}        21 
                    {txt}{c |}{res}     10.94       9.72 {txt}{c |}{res}     10.50 
{txt}{hline 20}{c +}{hline 22}{c +}{hline 10}
              Total {c |}{res}       128         72 {txt}{c |}{res}       200 
                    {txt}{c |}{res}    100.00     100.00 {txt}{c |}{res}    100.00 

{txt}          Pearson chi2({res}1{txt}) = {res}  0.0724  {txt} Pr = {res}0.788
Click to Open File:  {browse "A13T02.doc"}

{com}. 
. asdoc tab preference_adjusted_label trump_label, title(Table 2d: Cross-tabulations of response preference across associations - Total) col chi2 save(A13T02)
{txt}(File A13T02.doc already exists, option {bf:append} was assumed)

{c TLC}{hline 19}{c TRC}
{c |} Key{col 21}{c |}
{c LT}{hline 19}{c RT}
{c |}{space 5}{it:frequency}{col 21}{c |}
{c |}{space 1}{it:column percentage}{col 21}{c |}
{c BLC}{hline 19}{c BRC}

          RECODE of {c |}    RECODE of trump
preference_adjusted {c |} Not Trump      Trump {c |}     Total
{hline 20}{c +}{hline 22}{c +}{hline 10}
Prefer conventional {c |}{res}       380        147 {txt}{c |}{res}       527 
                    {txt}{c |}{res}     87.96      87.50 {txt}{c |}{res}     87.83 
{txt}{hline 20}{c +}{hline 22}{c +}{hline 10}
     Prefer nuclear {c |}{res}        52         21 {txt}{c |}{res}        73 
                    {txt}{c |}{res}     12.04      12.50 {txt}{c |}{res}     12.17 
{txt}{hline 20}{c +}{hline 22}{c +}{hline 10}
              Total {c |}{res}       432        168 {txt}{c |}{res}       600 
                    {txt}{c |}{res}    100.00     100.00 {txt}{c |}{res}    100.00 

{txt}          Pearson chi2({res}1{txt}) = {res}  0.0243  {txt} Pr = {res}0.876
Click to Open File:  {browse "A13T02.doc"}

{com}. 
. 
. 
. *** Appendix 13, Table 3 (contingency tables) - President party over treatment ***

. 
. 
. 
. * Generating a simplified version of the president variable

. 
. gen president_party = .
{txt}(600 missing values generated)

{com}. 
. replace president_party = 1 if president == 1
{txt}(168 real changes made)

{com}. 
. replace president_party = 1 if president == 3
{txt}(106 real changes made)

{com}. 
. replace president_party = 0 if president == 2
{txt}(23 real changes made)

{com}. 
. replace president_party = 0 if president == 4
{txt}(23 real changes made)

{com}. 
. 
. 
. * Generating a labelled version of the president_party variable

. 
. recode president_party (0=0 "Democrat") (1=1 "Republican"), generate(president_party_label)
{txt}(0 differences between {bf:president_party} and {bf:president_party_label})

{com}. 
. 
. 
. * Generating cross-tabs for president_party over preference by scenario

. 
. asdoc tab preference_adjusted_label president_party_label if scenario_n_label==0, title(Table 3a: Cross-tabulations of response preference across associations - Control) col chi2 save(A13T03)
{txt}
{c TLC}{hline 19}{c TRC}
{c |} Key{col 21}{c |}
{c LT}{hline 19}{c RT}
{c |}{space 5}{it:frequency}{col 21}{c |}
{c |}{space 1}{it:column percentage}{col 21}{c |}
{c BLC}{hline 19}{c BRC}

                    {c |}       RECODE of
          RECODE of {c |}    president_party
preference_adjusted {c |}  Democrat  Republica {c |}     Total
{hline 20}{c +}{hline 22}{c +}{hline 10}
Prefer conventional {c |}{res}        18         37 {txt}{c |}{res}        55 
                    {txt}{c |}{res}     81.82      75.51 {txt}{c |}{res}     77.46 
{txt}{hline 20}{c +}{hline 22}{c +}{hline 10}
     Prefer nuclear {c |}{res}         4         12 {txt}{c |}{res}        16 
                    {txt}{c |}{res}     18.18      24.49 {txt}{c |}{res}     22.54 
{txt}{hline 20}{c +}{hline 22}{c +}{hline 10}
              Total {c |}{res}        22         49 {txt}{c |}{res}        71 
                    {txt}{c |}{res}    100.00     100.00 {txt}{c |}{res}    100.00 

{txt}          Pearson chi2({res}1{txt}) = {res}  0.3461  {txt} Pr = {res}0.556
Click to Open File:  {browse "A13T03.doc"}

{com}. 
. asdoc tab preference_adjusted_label president_party_label if scenario_n_label==1, title(Table 3b: Cross-tabulations of response preference across associations - Ambiguity) col chi2 save(A13T03)
{txt}(File A13T03.doc already exists, option {bf:append} was assumed)

{c TLC}{hline 19}{c TRC}
{c |} Key{col 21}{c |}
{c LT}{hline 19}{c RT}
{c |}{space 5}{it:frequency}{col 21}{c |}
{c |}{space 1}{it:column percentage}{col 21}{c |}
{c BLC}{hline 19}{c BRC}

                    {c |}       RECODE of
          RECODE of {c |}    president_party
preference_adjusted {c |}  Democrat  Republica {c |}     Total
{hline 20}{c +}{hline 22}{c +}{hline 10}
Prefer conventional {c |}{res}        12         96 {txt}{c |}{res}       108 
                    {txt}{c |}{res}     92.31      86.49 {txt}{c |}{res}     87.10 
{txt}{hline 20}{c +}{hline 22}{c +}{hline 10}
     Prefer nuclear {c |}{res}         1         15 {txt}{c |}{res}        16 
                    {txt}{c |}{res}      7.69      13.51 {txt}{c |}{res}     12.90 
{txt}{hline 20}{c +}{hline 22}{c +}{hline 10}
              Total {c |}{res}        13        111 {txt}{c |}{res}       124 
                    {txt}{c |}{res}    100.00     100.00 {txt}{c |}{res}    100.00 

{txt}          Pearson chi2({res}1{txt}) = {res}  0.3509  {txt} Pr = {res}0.554
Click to Open File:  {browse "A13T03.doc"}

{com}. 
. asdoc tab preference_adjusted_label president_party_label if scenario_n_label==2, title(Table 3c: Cross-tabulations of response preference across associations - Explicit) col chi2 save(A13T03)
{txt}(File A13T03.doc already exists, option {bf:append} was assumed)

{c TLC}{hline 19}{c TRC}
{c |} Key{col 21}{c |}
{c LT}{hline 19}{c RT}
{c |}{space 5}{it:frequency}{col 21}{c |}
{c |}{space 1}{it:column percentage}{col 21}{c |}
{c BLC}{hline 19}{c BRC}

                    {c |}       RECODE of
          RECODE of {c |}    president_party
preference_adjusted {c |}  Democrat  Republica {c |}     Total
{hline 20}{c +}{hline 22}{c +}{hline 10}
Prefer conventional {c |}{res}        10        104 {txt}{c |}{res}       114 
                    {txt}{c |}{res}     90.91      91.23 {txt}{c |}{res}     91.20 
{txt}{hline 20}{c +}{hline 22}{c +}{hline 10}
     Prefer nuclear {c |}{res}         1         10 {txt}{c |}{res}        11 
                    {txt}{c |}{res}      9.09       8.77 {txt}{c |}{res}      8.80 
{txt}{hline 20}{c +}{hline 22}{c +}{hline 10}
              Total {c |}{res}        11        114 {txt}{c |}{res}       125 
                    {txt}{c |}{res}    100.00     100.00 {txt}{c |}{res}    100.00 

{txt}          Pearson chi2({res}1{txt}) = {res}  0.0013  {txt} Pr = {res}0.972
Click to Open File:  {browse "A13T03.doc"}

{com}. 
. asdoc tab preference_adjusted_label president_party_label, title(Table 3d: Cross-tabulations of response preference across associations - Total) col chi2 save(A13T03)
{txt}(File A13T03.doc already exists, option {bf:append} was assumed)

{c TLC}{hline 19}{c TRC}
{c |} Key{col 21}{c |}
{c LT}{hline 19}{c RT}
{c |}{space 5}{it:frequency}{col 21}{c |}
{c |}{space 1}{it:column percentage}{col 21}{c |}
{c BLC}{hline 19}{c BRC}

                    {c |}       RECODE of
          RECODE of {c |}    president_party
preference_adjusted {c |}  Democrat  Republica {c |}     Total
{hline 20}{c +}{hline 22}{c +}{hline 10}
Prefer conventional {c |}{res}        40        237 {txt}{c |}{res}       277 
                    {txt}{c |}{res}     86.96      86.50 {txt}{c |}{res}     86.56 
{txt}{hline 20}{c +}{hline 22}{c +}{hline 10}
     Prefer nuclear {c |}{res}         6         37 {txt}{c |}{res}        43 
                    {txt}{c |}{res}     13.04      13.50 {txt}{c |}{res}     13.44 
{txt}{hline 20}{c +}{hline 22}{c +}{hline 10}
              Total {c |}{res}        46        274 {txt}{c |}{res}       320 
                    {txt}{c |}{res}    100.00     100.00 {txt}{c |}{res}    100.00 

{txt}          Pearson chi2({res}1{txt}) = {res}  0.0072  {txt} Pr = {res}0.933
Click to Open File:  {browse "A13T03.doc"}

{com}. 
. 
. 
. *************************************************

. 
. *** Replication of the results in Appendix 14 ***

. 
. *************************************************

. 
. 
. 
. *** Appendix 14, Figure 1 (coefficient plot) - Preference (DV), no subset ***

. 
. 
. 
. * Running the ordinal logit model (Model 5)

. 
. ologit preference_ordinal i.scenario_n 

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-566.68502}  
Iteration 1:{space 3}log likelihood = {res:-565.28545}  
Iteration 2:{space 3}log likelihood = {res:-565.28403}  
Iteration 3:{space 3}log likelihood = {res:-565.28403}  
{res}
{txt}{col 1}Ordered logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:600}
{txt}{col 57}{lalign 13:LR chi2({res:2})}{col 70} = {res}{ralign 6:2.80}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.2464}
{txt}{col 1}{lalign 14:Log likelihood}{col 15} = {res}{ralign 10:-565.28403}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.0025}

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}preference~al{col 15}{c |} Coefficient{col 27}  Std. err.{col 39}      z{col 47}   P>|z|{col 55}     [95% con{col 68}f. interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}scenario_n {c |}
{space 11}1  {c |}{col 15}{res}{space 2}-.3085967{col 27}{space 2} .2056927{col 38}{space 1}   -1.50{col 47}{space 3}0.134{col 55}{space 4}-.7117469{col 68}{space 3} .0945535
{txt}{space 11}2  {c |}{col 15}{res}{space 2}-.2770165{col 27}{space 2} .2026663{col 38}{space 1}   -1.37{col 47}{space 3}0.172{col 55}{space 4}-.6742352{col 68}{space 3} .1202022
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}/cut1 {c |}{col 15}{res}{space 2} .4438975{col 27}{space 2} .1407029{col 55}{space 4} .1681249{col 68}{space 3}   .71967
{txt}{space 8}/cut2 {c |}{col 15}{res}{space 2} 1.791983{col 27}{space 2} .1649771{col 55}{space 4} 1.468634{col 68}{space 3} 2.115332
{txt}{space 8}/cut3 {c |}{col 15}{res}{space 2} 3.084568{col 27}{space 2} .2421444{col 55}{space 4} 2.609973{col 68}{space 3} 3.559162
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. * Storing the estimates (Model 5)

. 
. estimates store M5

. 
. 
. 
. * Running the ordinal logit model with controls (Model 6)

. 
. ologit preference_ordinal i.scenario_n i.male c.age c.income i.education_bin i.party

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-565.83191}  
Iteration 1:{space 3}log likelihood = {res:-543.36824}  
Iteration 2:{space 3}log likelihood = {res:-543.03959}  
Iteration 3:{space 3}log likelihood = {res:-543.03938}  
Iteration 4:{space 3}log likelihood = {res:-543.03938}  
{res}
{txt}{col 1}Ordered logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:598}
{txt}{col 57}{lalign 13:LR chi2({res:8})}{col 70} = {res}{ralign 6:45.59}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.0000}
{txt}{col 1}{lalign 14:Log likelihood}{col 15} = {res}{ralign 10:-543.03938}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.0403}

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}preference~al{col 15}{c |} Coefficient{col 27}  Std. err.{col 39}      z{col 47}   P>|z|{col 55}     [95% con{col 68}f. interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}scenario_n {c |}
{space 11}1  {c |}{col 15}{res}{space 2}-.3390136{col 27}{space 2} .2112843{col 38}{space 1}   -1.60{col 47}{space 3}0.109{col 55}{space 4}-.7531233{col 68}{space 3} .0750961
{txt}{space 11}2  {c |}{col 15}{res}{space 2} -.209249{col 27}{space 2}  .207805{col 38}{space 1}   -1.01{col 47}{space 3}0.314{col 55}{space 4}-.6165393{col 68}{space 3} .1980414
{txt}{space 13} {c |}
{space 7}1.male {c |}{col 15}{res}{space 2}-.6209948{col 27}{space 2} .1749624{col 38}{space 1}   -3.55{col 47}{space 3}0.000{col 55}{space 4}-.9639148{col 68}{space 3}-.2780749
{txt}{space 10}age {c |}{col 15}{res}{space 2}-.0220771{col 27}{space 2} .0063351{col 38}{space 1}   -3.48{col 47}{space 3}0.000{col 55}{space 4}-.0344935{col 68}{space 3}-.0096606
{txt}{space 7}income {c |}{col 15}{res}{space 2} .0682217{col 27}{space 2} .0258665{col 38}{space 1}    2.64{col 47}{space 3}0.008{col 55}{space 4} .0175242{col 68}{space 3} .1189191
{txt}1.education~n {c |}{col 15}{res}{space 2}-.2459631{col 27}{space 2} .1841624{col 38}{space 1}   -1.34{col 47}{space 3}0.182{col 55}{space 4}-.6069148{col 68}{space 3} .1149887
{txt}{space 13} {c |}
{space 8}party {c |}
{space 11}1  {c |}{col 15}{res}{space 2}-.5959472{col 27}{space 2}  .213584{col 38}{space 1}   -2.79{col 47}{space 3}0.005{col 55}{space 4}-1.014564{col 68}{space 3}-.1773303
{txt}{space 11}2  {c |}{col 15}{res}{space 2}-.6320274{col 27}{space 2} .2108099{col 38}{space 1}   -3.00{col 47}{space 3}0.003{col 55}{space 4}-1.045207{col 68}{space 3}-.2188476
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}/cut1 {c |}{col 15}{res}{space 2}-.7100289{col 27}{space 2} .3948886{col 55}{space 4}-1.483996{col 68}{space 3} .0639385
{txt}{space 8}/cut2 {c |}{col 15}{res}{space 2}  .718538{col 27}{space 2} .3960042{col 55}{space 4} -.057616{col 68}{space 3} 1.494692
{txt}{space 8}/cut3 {c |}{col 15}{res}{space 2} 2.039465{col 27}{space 2} .4300693{col 55}{space 4} 1.196545{col 68}{space 3} 2.882386
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. * Storing the estimates (Model 6)

. 
. estimates store M6

. 
. 
. 
. * Generating the coefficient plot (Appendix 14, Figure 1)

. 
. coefplot M5, bylabel(Model 5) || M6, bylabel (Model 6) ||, xline(0) coeflabels(1.scenario_n = "{c -(}bf:Treatment (ambiguity – control){c )-}" 2.scenario_n = "{c -(}bf:Treatment (explicit – control){c )-}" 1.male = "Gender (male)" age = "Age" income = "Income" 1.education_bin = "Education (university degree)" 1.party = "Party (Democrat – Republican)" 2.party = "Party (Independent – Republican)")
{res}
{com}. 
. 
. 
. * Exporting the coefficient plot (Appendix 14, Figure 1)

. 
. graph export A14F01.png
{txt}{p 0 4 2}
file {bf}
A14F01.png{rm}
saved as
PNG
format
{p_end}

{com}. 
. 
. 
. *** Appendix 14, Figure 2 (catplot) - Preference over treatment ***

. 
. 
. 
. * Generating a catplot for preference_adjusted over scenario_n_label

. 
. catplot preference_adjusted scenario_n_label, percent(scenario_n_label) ytitle ("Percent of Respondents by Preference", size(small)) intensity(75) asyvars stack blabel(bar, pos(center) format(%4.0f) size(small)) legend(rows(1) stack size(small) order(1 "Prefer conventional" 2 "Prefer nuclear") symplacement(center))
{res}
{com}. 
. 
. 
. * Exporting the catplot (Appendix 14, Figure 2)

. 
. graph export A14F02.png
{txt}{p 0 4 2}
file {bf}
A14F02.png{rm}
saved as
PNG
format
{p_end}

{com}. 
. 
. 
. *************************************************

. 
. *** Replication of the results in Appendix 15 ***

. 
. *************************************************

. 
. 
. 
. **** Appendix 15, Figure 1 - Credibility of non-nuclear response (DV), no subset ***

. 
. 
. 
. * Running the ordinal logit model (Model 1)

. 
. ologit credibility_nonnuclear i.scenario_n

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-882.89768}  
Iteration 1:{space 3}log likelihood = {res:-881.00035}  
Iteration 2:{space 3}log likelihood = {res:-880.99953}  
Iteration 3:{space 3}log likelihood = {res:-880.99953}  
{res}
{txt}{col 1}Ordered logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:600}
{txt}{col 57}{lalign 13:LR chi2({res:2})}{col 70} = {res}{ralign 6:3.80}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.1498}
{txt}{col 1}{lalign 14:Log likelihood}{col 15} = {res}{ralign 10:-880.99953}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.0021}

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}credibility~r{col 15}{c |} Coefficient{col 27}  Std. err.{col 39}      z{col 47}   P>|z|{col 55}     [95% con{col 68}f. interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}scenario_n {c |}
{space 11}1  {c |}{col 15}{res}{space 2}-.0201995{col 27}{space 2} .1789412{col 38}{space 1}   -0.11{col 47}{space 3}0.910{col 55}{space 4}-.3709179{col 68}{space 3} .3305188
{txt}{space 11}2  {c |}{col 15}{res}{space 2}-.3138467{col 27}{space 2} .1801965{col 38}{space 1}   -1.74{col 47}{space 3}0.082{col 55}{space 4}-.6670253{col 68}{space 3} .0393319
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}/cut1 {c |}{col 15}{res}{space 2}-3.178641{col 27}{space 2} .2247691{col 55}{space 4} -3.61918{col 68}{space 3}-2.738101
{txt}{space 8}/cut2 {c |}{col 15}{res}{space 2}-1.462767{col 27}{space 2} .1469307{col 55}{space 4}-1.750745{col 68}{space 3}-1.174788
{txt}{space 8}/cut3 {c |}{col 15}{res}{space 2} .0859863{col 27}{space 2} .1314035{col 55}{space 4}-.1715599{col 68}{space 3} .3435324
{txt}{space 8}/cut4 {c |}{col 15}{res}{space 2} 1.240578{col 27}{space 2} .1422918{col 55}{space 4} .9616915{col 68}{space 3} 1.519465
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. * Storing the estimates (Model 1)

. 
. estimates store M1

. 
. 
. 
. * Running the ordinal logit model with controls (Model 2)

. 
. ologit credibility_nonnuclear i.scenario_n i.male c.age c.income i.education_bin i.party

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-880.74339}  
Iteration 1:{space 3}log likelihood = {res: -852.6633}  
Iteration 2:{space 3}log likelihood = {res:-852.47939}  
Iteration 3:{space 3}log likelihood = {res:-852.47928}  
Iteration 4:{space 3}log likelihood = {res:-852.47928}  
{res}
{txt}{col 1}Ordered logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:598}
{txt}{col 57}{lalign 13:LR chi2({res:8})}{col 70} = {res}{ralign 6:56.53}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.0000}
{txt}{col 1}{lalign 14:Log likelihood}{col 15} = {res}{ralign 10:-852.47928}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.0321}

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}credibility~r{col 15}{c |} Coefficient{col 27}  Std. err.{col 39}      z{col 47}   P>|z|{col 55}     [95% con{col 68}f. interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}scenario_n {c |}
{space 11}1  {c |}{col 15}{res}{space 2}-.0240802{col 27}{space 2} .1812435{col 38}{space 1}   -0.13{col 47}{space 3}0.894{col 55}{space 4} -.379311{col 68}{space 3} .3311506
{txt}{space 11}2  {c |}{col 15}{res}{space 2}-.3927434{col 27}{space 2} .1826573{col 38}{space 1}   -2.15{col 47}{space 3}0.032{col 55}{space 4}-.7507452{col 68}{space 3}-.0347416
{txt}{space 13} {c |}
{space 7}1.male {c |}{col 15}{res}{space 2} .9291678{col 27}{space 2} .1521826{col 38}{space 1}    6.11{col 47}{space 3}0.000{col 55}{space 4} .6308954{col 68}{space 3}  1.22744
{txt}{space 10}age {c |}{col 15}{res}{space 2}  .016459{col 27}{space 2} .0052208{col 38}{space 1}    3.15{col 47}{space 3}0.002{col 55}{space 4} .0062264{col 68}{space 3} .0266917
{txt}{space 7}income {c |}{col 15}{res}{space 2}-.0393354{col 27}{space 2} .0218456{col 38}{space 1}   -1.80{col 47}{space 3}0.072{col 55}{space 4}-.0821521{col 68}{space 3} .0034813
{txt}1.education~n {c |}{col 15}{res}{space 2} .1611672{col 27}{space 2} .1581479{col 38}{space 1}    1.02{col 47}{space 3}0.308{col 55}{space 4} -.148797{col 68}{space 3} .4711314
{txt}{space 13} {c |}
{space 8}party {c |}
{space 11}1  {c |}{col 15}{res}{space 2} .3521007{col 27}{space 2} .1868453{col 38}{space 1}    1.88{col 47}{space 3}0.060{col 55}{space 4}-.0141094{col 68}{space 3} .7183108
{txt}{space 11}2  {c |}{col 15}{res}{space 2} .2763912{col 27}{space 2} .1838117{col 38}{space 1}    1.50{col 47}{space 3}0.133{col 55}{space 4}-.0838731{col 68}{space 3} .6366555
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}/cut1 {c |}{col 15}{res}{space 2}-2.222177{col 27}{space 2} .3761179{col 55}{space 4}-2.959355{col 68}{space 3}   -1.485
{txt}{space 8}/cut2 {c |}{col 15}{res}{space 2}-.4553472{col 27}{space 2} .3389703{col 55}{space 4}-1.119717{col 68}{space 3} .2090224
{txt}{space 8}/cut3 {c |}{col 15}{res}{space 2} 1.180045{col 27}{space 2} .3403021{col 55}{space 4} .5130651{col 68}{space 3} 1.847025
{txt}{space 8}/cut4 {c |}{col 15}{res}{space 2} 2.406447{col 27}{space 2} .3509929{col 55}{space 4} 1.718514{col 68}{space 3}  3.09438
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. * Storing the estimates (Model 2)

. 
. estimates store M2

. 
. 
. 
. * Generating the coefficient plot (Appendix 15, Figure 1)

. 
. coefplot M1, bylabel(Model 1) || M2, bylabel (Model 2) ||, xline(0) coeflabels(1.scenario_n = "{c -(}bf:Treatment (ambiguity – control){c )-}" 2.scenario_n = "{c -(}bf:Treatment (explicit – control){c )-}" 1.male = "Gender (male)" age = "Age" income = "Income" 1.education_bin = "Education (university degree)" 1.party = "Party (Democrat – Republican)" 2.party = "Party (Independent – Republican)")
{res}
{com}. 
. 
. 
. * Exporting the coefficient plot (Appendix 15, Figure 1)

. 
. graph export A15F01.png
{txt}{p 0 4 2}
file {bf}
A15F01.png{rm}
saved as
PNG
format
{p_end}

{com}. 
. 
. 
. *** Appendix 15, Figure 2 - Credibility of non-nuclear response across treatments ***

. 
. 
. 
. * Generating a simplified version of credibility_nonnuclear

. 
. gen credibility_nonnuclear_adjusted = 0

. 
. replace credibility_nonnuclear_adjusted = 1 if credibility_nonnuclear == 3
{txt}(205 real changes made)

{com}. 
. replace credibility_nonnuclear_adjusted = 2 if credibility_nonnuclear == 4
{txt}(147 real changes made)

{com}. 
. replace credibility_nonnuclear_adjusted = 2 if credibility_nonnuclear == 5
{txt}(124 real changes made)

{com}. 
. 
. 
. * Generating a catplot of credibility_nonnuclear_adjusted over scenario_n_label

. 
. catplot credibility_nonnuclear_adjusted scenario_n_label, percent (scenario_n_label) ytitle ("Percent of Respondents by Credibility", size(small)) intensity(75) asyvars stack blabel(bar, pos(center) format(%4.0f) size(small)) legend(rows(1) stack size(small) order(1 "Weaken credibility" 2 "Neither weaken nor bolster" 3 "Bolster credibility") symplacement(center))
{res}
{com}. 
. 
. 
. * Exporting the catplot (Appendix 15, Figure 2)

. 
. graph export A15F02.png
{txt}{p 0 4 2}
file {bf}
A15F02.png{rm}
saved as
PNG
format
{p_end}

{com}. 
. 
. 
. ****************************

. 
. *** End replication here ***

. 
. ****************************

. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\ondre\OneDrive\Plocha\RnP\Revisions\Dataverse\svr_jeps_replication_log4.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}20 Jan 2023, 13:22:05
{txt}{.-}
{smcl}
{txt}{sf}{ul off}